Machine Learning Engineer II - Operations

Milwaukee Electric Tool Corporation is hiring an Machine Learning Engineer II - Operations for an onsite role in Milwaukee, WI. In this position, you’ll help design, build, and deploy machine learning solutions that strengthen how Milwaukee Tool manufactures and services its products. You’ll support end-to-end work across the ML lifecycle, collaborating with operations-focused teams to deliver measurable value where models are used.

What you’ll do

• Design, develop, and deploy machine learning solutions to improve manufacturing and service processes.
• Partner cross-functionally with operations, quality, supply chain, engineering, and service teams to deliver data-driven solutions for real-world business and operational challenges across global environments.
• Own the full ML lifecycle, from data engineering and model development to deployment and monitoring on Azure and Databricks.
• Work with Global and Service Teams to deploy, validate, and support ML solutions in operational settings to ensure models produce measurable impact.
• Build and implement data-driven solutions in operational environments across the organization.

What you bring

• Bachelor of Science degree in Computer Science, Computer Engineering, Electrical Engineering, or another scientific or engineering discipline.
• Completed coursework or specialization in Machine Learning and/or Data Science using deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• At least 1 year of hands-on experience applying machine learning principles and algorithms to dynamic, real-world problems.
• Demonstrated experience applying fundamental ML methods in non-coursework settings, including unsupervised or supervised learning, classification/regression, dimensionality reduction, and model optimization.
• Experience with AI/ML approaches such as CNNs, transformers, or computer vision.
• Proficiency in big data transformation using Spark, SQL, and Python (including NumPy, pandas, scikit-learn, Matplotlib).
• Solid mathematical foundation in statistics, linear algebra, calculus, and optimization.
• Experience deploying ML using CI/CD pipelines with tools such as Azure, Databricks, and MLFlow, plus familiarity with edge devices (GPU, containerization, Linux).
• Excellent problem-solving and technical communication skills, with the ability to explain complex ML deployments to non-technical audiences.
• Experience collaborating with global teams, including willingness to adjust working hours to align with international time zones.

Tools and technologies you’ll work with

• PyTorch, TensorFlow, Keras
• Spark, SQL, Python, NumPy, pandas, scikit-learn, Matplotlib
• Azure, Databricks, MLFlow, CI/CD
• GPU, Containerization, Linux
• CNNs, transformers

Preferred

• Master’s degree or PhD in Machine Learning or a related field.
• At least three years of hands-on experience applying ML principles and algorithms to dynamic, real-world problems.
• Experience with time-series modeling (demand forecasting, predictive maintenance, yield prediction, or process anomaly detection).
• Computer vision experience for use cases such as defect detection, missing part detection, part quality inspection, or part counting.
• Proven track record of developing, deploying, and scaling AI/ML tied to measurable operations outcomes (for example: scrap reduction, throughput, OEE, on-time delivery, inventory turns).
• Desktop and/or web application development experience that helps put models in the hands of plant and operations users.
• Hands-on data engineering experience building pipelines on Databricks/Spark using large operational datasets (MES, ERP, SCADA, IoT/Sensor Telemetry).
• Experience applying generative AI or LLMs to operations problems such as knowledge retrieval, document processing, or assistive tooling for plant teams.
• Experience developing and using MLOps pipelines to deploy, monitor, and scale ML models in production.
• Experience developing and deploying machine learning algorithms to edge environments.

Benefits

• Robust health, dental and vision insurance plans.
• Generous 401 (K) savings plan.
• Education assistance.
• On-site wellness, fitness center, food, and coffee service.